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An intelligent solar powered battery buffered EV charging station with solar electricity forecasting and EV charging load projection functions

机译:具有太阳能预测和电动汽车充电负荷预测功能的智能太阳能电池缓冲电动汽车充电站

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An intelligent energy management approach for a solar powered EV charging station with energy storage has been studied and demonstrated for a level 2 charger at the University of California-Davis West Village. The approach introduces solar PV electrical energy forecasting and EV charging demand projection to optimize the energy management of the charging station. The percentage of cloud cover is extracted from a weather forecast website for estimating the available PV electrical energy. A linear fit of the historical EV charging load from the same day of the week over the previous six weeks is employed for extracting the charging pattern of the workplace EV charging station. Both simulations and actual operation show that intelligent energy management for a charging station with a buffer battery can reduce impacts of the EV charging system on utility grids in terms of peak power demand and energy exchange, reduce grid system losses, and benefit the charging station owner through the Time-of-Use rate plans.
机译:加利福尼亚大学戴维斯分校西村的2级充电器已研究并论证了带储能的太阳能EV充电站的智能能源管理方法。该方法引入了太阳能光伏电能预测和电动汽车充电需求预测,以优化充电站的能源管理。从天气预报网站中提取云量的百分比,以估算可用的PV电能。使用过去六个星期中的一周中的同一天的历史电动汽车充电负荷的线性拟合来提取工作场所电动汽车充电站的充电模式。仿真和实际操作均表明,具有缓冲电池的充电站的智能能源管理可以从峰值功率需求和能量交换方面减少EV充电系统对公用电网的影响,减少电网系统的损耗,并使充电站所有者受益通过使用时间费率计划。

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